CN116931037B - Data correction method, device and equipment for occultation detection - Google Patents

Abstract

Embodiments of the present application provide a data correction method, device and equipment for occultation detection, which belongs to the field of space detection technology. The method includes: obtaining a first sampling time and a second sampling time. The first sampling time is included in the first sampling time of occultation detection. The sampling time in the working mode, the second sampling time includes the sampling time in the second working mode of the occultation detection; determine the matching point between the first sampling time and the second sampling time, the matching point includes the first time that the interval time is less than the target threshold The sampling time and the second sampling time; according to the sampling data at the sampling time included in the matching point, determine the deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode; correct the second time based on the deviation parameter. Sampling data at the sampling time. Therefore, the embodiments of the present application can solve the problem in the prior art that during occultation detection, switching between the PLL mode and the OL mode may produce switching system deviations, resulting in an increase in occultation observation errors.

Description

A method, device and equipment for correcting data of occultation detection

Technical Field

The present application relates to the field of space detection technology, and in particular to a data correction method, device and equipment for occultation detection.

Background Art

The Global Navigation Satellite System (GNSS) radio occultation atmospheric sounding technology refers to installing a GNSS dual-frequency receiver on a low-orbit satellite to receive GNSS signals. Among them, due to the influence of atmospheric water vapor density and other factors, the vertical refractive index of the propagation medium changes, and the radio wave path will bend when the GNSS navigation signal passes through the Earth's atmospheric profile and ionosphere. Based on the amplitude and phase delay of the measured GNSS occultation observation data, the atmospheric refractive index can be calculated, and the atmospheric density, pressure and temperature can be derived.

There are two main tracking modes for GNSS Earth atmospheric occultation detection, namely the closed loop (Phase-LockedLoop, PLL) mode and the open loop (Open Loop, OL) mode. The PLL mode means that the receiver uses a phase-locked loop to track the phase changes of the satellite signal. Specifically, the receiver measures the phase of the satellite signal and generates an "ideal" reference signal whose frequency and phase correspond to the expected satellite signal. Then, the phase error is calculated by subtracting the phase of the satellite signal from the phase of the generated reference signal. Finally, the phase error is used to adjust the frequency and phase of the reference signal generated by the receiver so that the phases of the two signals are consistent. This process is achieved by controlling a voltage-controlled oscillator to continuously correct the phase difference of the signal to minimize the error.

However, due to the complex calculation and real-time correction, PLL mode may be more sensitive to noise and interference. Therefore, PLL mode can usually provide higher tracking accuracy, but requires more computing resources and time to implement.

Among them, due to the richer water vapor in the troposphere, multipath propagation will occur when tracking GNSS occultation signals in PLL mode, causing strong disturbances in the amplitude and phase of the received signal, which may lead to wrong tracking or even loss of lock. To solve this problem, OL tracking technology is proposed.

The OL mode does not use a phase-locked loop, but uses the Doppler model and pseudo-range model of GNSS or Low Earth Orbit (LEO) for climate forecasting (such as predicting orbits and atmospheric refractive index) to track the signal, thereby calculating the error between the measured signal characteristics and the expected characteristics, which is used to adjust the receiver frequency. Therefore, the OL mode will not be affected by signal changes, has the ability to track multiple phases and amplitudes (caused by atmospheric multipath), and can more conveniently detect rising occultation events. Among them, the accuracy of the Doppler frequency model can reach ±10Hz, so the OL mode can track and receive weak GNSS signals within a very narrow bandwidth, which not only solves the tracking of weak signals, but also solves the tracking problem of rising occultation, thereby greatly increasing the number of occultation observation profiles and reducing the minimum detection altitude of each occultation event.

However, although the OL technology is simpler and faster, it has stronger observation capabilities in the lower troposphere and tracking capabilities of ascending occultation events. However, receivers that only use the OL tracking method sample the raw data of the frequency-converted complex signal at the signal and mode frequencies, and the carrier phase signal is affected by navigation data modulation (NDM). There is a lack of a continuous correction mechanism. Therefore, the OL mode may be more sensitive to signal instability and interference, and the measurement accuracy may be relatively low. Therefore, during the tracking of an occultation event, the occultation receiver can alternate between the PLL working mode and the OL working mode to balance accuracy and efficiency. For example, the PLL observation method is used at an occultation tangent point altitude of more than 10 km, and the OL observation method is used below 10 km.

However, when using PLL and OL modes alternately, since the open-loop carrier phase and closed-loop carrier phase recorded are two independent tracks, switching between PLL mode and OL mode may cause the following two problems:

1. Switching system deviation: that is, mode adaptability issues, which may cause the tracking mode to not switch immediately when actually needed, thus affecting the accuracy and continuity of the signal.

2. Increased error: that is, there may be deviations in the carrier phase under different modes, which will lead to increased errors in occultation observations, especially in applications that require high-precision occultation detection.

It can be seen from the above that in the prior art, during occultation detection, switching between the PLL mode and the OL mode may cause a switching system deviation and lead to an increase in the occultation observation error.

Summary of the invention

The embodiments of the present application provide a data correction method, device and equipment for occultation detection to solve the problem in the prior art that during occultation detection, switching between PLL mode and OL mode may cause switching system deviation and lead to increased occultation observation errors.

In a first aspect, an embodiment of the present application provides a data correction method for occultation detection, the method comprising:

Acquire a first sampling time and a second sampling time, wherein the first sampling time includes a sampling time in a first working mode of occultation detection, and the second sampling time includes a sampling time in a second working mode of occultation detection;

Determine a matching point between the first sampling moment and the second sampling moment, wherein the matching point includes the first sampling moment and the second sampling moment whose interval time is less than a target threshold;

Determine, according to the sampling data at the sampling time included in the matching point, a deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode;

The sampling data at the second sampling time is corrected according to the deviation parameter.

In a second aspect, an embodiment of the present application provides a data correction device for occultation detection, the device comprising:

An acquisition module, configured to acquire a first sampling moment and a second sampling moment, wherein the first sampling moment includes a sampling moment in a first working mode of occultation detection, and the second sampling moment includes a sampling moment in a second working mode of occultation detection;

A matching module, configured to determine a matching point between the first sampling moment and the second sampling moment, wherein the matching point includes a first sampling moment and a second sampling moment whose interval time is less than a target threshold;

A parameter determination module, used to determine a deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode according to the sampling data at the sampling moment included in the matching point;

A correction module is used to correct the sampling data at the second sampling moment according to the deviation parameter.

In a third aspect, an embodiment of the present application provides an occultation receiver, comprising the above-mentioned data correction device for occultation detection.

In a fourth aspect, an embodiment of the present application provides an electronic device, the electronic device comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

Memory, used to store computer programs;

The processor is used to implement the steps in the data correction method for occultation detection when executing the program stored in the memory.

In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the data correction method for occultation detection are implemented.

The embodiments of the present application include at least the following technical effects:

The technical solution of the embodiment of the present application can obtain the first sampling moment in the first working mode of occultation detection and the second sampling moment in the second working mode of occultation detection, so as to determine the matching point between the first sampling moment and the second sampling moment, that is, determine the first sampling moment and the second sampling moment whose interval is less than the target threshold, and then determine the deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode according to the sampling data of the sampling moments included in the matching points, and then correct the sampling data at the second sampling moment according to the deviation parameter.

It can be seen that in the embodiment of the present application, the sampling moments in the first working mode and the second working mode with an interval time less than the target threshold (i.e., the sampling moments with a shorter interval time) can be determined, and then based on the sampling data of the sampling moments in the two working modes with an interval time less than the target threshold, the deviation parameters of the sampling data in the two working modes can be determined, and then the sampling data in the second working mode can be corrected according to the deviation parameters. In this way, when the occultation detection is switched from the first working mode to the second working mode, the sampling data can be better connected, and the corrected sampling data can be more accurate, thereby reducing the switching system deviation of the working mode and the occultation observation error. That is, the embodiment of the present application lays a foundation for achieving seamless connection from the first working mode to the second working mode.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art.

FIG1 is a schematic flow chart of a data correction method for occultation detection provided in an embodiment of the present application;

FIG2 is a schematic diagram showing the principle of determining matching points in implementation mode 1;

FIG3 is a schematic diagram showing the principle of determining matching points in the second implementation mode;

FIG4 is a schematic diagram showing the principle of determining matching points in implementation mode 3;

FIG5 is a schematic diagram showing the principle of determining matching points in implementation mode 4;

FIG6 is a structural block diagram of a data correction device for occultation detection provided by an embodiment of the present application;

FIG. 7 is a block diagram of an electronic device provided in an embodiment of the present application.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

It should be understood that the references to "one embodiment" or "an embodiment" throughout the specification mean that the specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present application. Therefore, the references to "in one embodiment" or "in an embodiment" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

In the various embodiments of the present application, it should be understood that the size of the serial numbers of the following processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

In the first aspect, referring to FIG. 1 , a flowchart of a method for data correction of occultation detection in an embodiment of the present application is shown. The method may include the following steps 101 to 104:

Step 101: Obtain a first sampling time and a second sampling time.

The first sampling time includes the sampling time in the first working mode of occultation detection, and the second sampling time includes the sampling time in the second working mode of occultation detection.

As can be seen from step 101, in the embodiment of the present application, it is necessary to obtain the sampling moments in different working modes of occultation detection. For example, the first sampling moment in the first working mode includes , , , … ; The second sampling time in the second working mode includes , , , … Here, the sampling frequency in the first working mode and the sampling frequency in the second working mode may be the same or different, n1 and n2 are both positive integers, and n1 and n2 may be the same or different.

Step 102: Determine a matching point between the first sampling time and the second sampling time.

The matching points include a first sampling moment and a second sampling moment whose interval time is less than a target threshold.

During occultation detection, there is an overlapping area between the sampling times of the first working mode and the second working mode, that is, the first sampling moment and the second sampling moment exist in the same time interval between the above-mentioned first sampling moment and the second sampling moment. In this way, the sampling data in the first working mode and the sampling data in the second working mode exist in the interval at the same time. Therefore, in the embodiment of the present application, the matching point of the first sampling moment and the second sampling moment can be determined, that is, the first sampling moment and the second sampling moment whose interval time is less than the target threshold are determined, so as to determine the connection point between the first working mode and the second working mode.

As can be seen from step 102, in the embodiment of the present application, the first sampling moment and the second sampling moment whose interval time is less than the target threshold can be obtained from the multiple first sampling moments and the second sampling moments obtained, and these two moments constitute the above-mentioned matching point, that is, the first working mode and the second working mode are connected at the matching point. It can be seen that in the embodiment of the present application, the interval time between the first sampling moment and the second sampling moment included in the matching point is less than the target threshold, that is, the interval time between the two is short, and therefore, the switching time from the first working mode to the second working mode is short. In this way, the embodiment of the present application can shorten the switching delay from the first working mode to the second working mode, thereby reducing the switching system deviation, so that the sampling data in the first working mode and the sampling data in the second working mode can be better connected.

Step 103: Determine a deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode according to the sampling data at the sampling time included in the matching point.

Among them, the interval time between the first sampling moment and the second sampling time included in the matching point is less than the target threshold, that is, the interval time between the two is short. Therefore, if from an ideal perspective, if these two moments are the same moment, then the data collected at these two moments should be equal, but because the first sampling moment collects data in the first working mode, and the second sampling moment collects data in the second working mode, and the methods or principles used by the two working modes to collect data are different, there is a certain deviation in the data collected at these two moments. Therefore, when the two sampling moments included in the matching point are separated by a certain time, the deviation of the data collected at these two sampling moments is increased. In this way, the deviation parameter of the data between the two working modes can be calculated based on the sampling data of the two sampling moments included in the matching point, so that when switching from the first working mode to the second working mode, the sampling data in the second working mode can be corrected according to the deviation parameter.

In addition, the sampling data at the sampling moment may include carrier phase observations, that is, in the first working mode and the second working mode of occultation detection, carrier phase observations may be collected at the sampling moment.

Step 104: Correcting the sampling data at the second sampling time according to the deviation parameter.

Among them, before the second sampling moment included in the above matching point, there is already sampling data of the first sampling moment. Therefore, optionally, in step 104, according to the deviation parameter, the sampling data of the second sampling moment after the second sampling moment included in the matching point among the multiple second sampling moments obtained in step 101 is corrected. For example, the second sampling moment includes , , , … ,and The second sampling time that belongs to the matching point is then corrected only … In this way, only necessary sampling data can be corrected, thereby reducing the processing flow and shortening the processing time.

It can be seen from the above steps 101 to 103 that in the embodiment of the present application, the sampling moments at which the interval time between the first working mode and the second working mode is less than the target threshold (i.e., the sampling moments with a shorter interval time) can be determined, and then based on the sampling data of the sampling moments at which the interval time is less than the target threshold in the two working modes, the deviation parameters of the sampling data in the two working modes are determined, and then the sampling data in the second working mode is corrected according to the deviation parameters. In this way, when the occultation detection is switched from the first working mode to the second working mode, the sampling data can be better connected, and the corrected sampling data is more accurate, thereby reducing the switching system deviation of the working mode and the occultation observation error. That is, the embodiment of the present application lays the foundation for achieving seamless connection from the first working mode to the second working mode.

In an optional embodiment of the present application, the “determining a matching point between the first sampling time and the second sampling time” in the above step 102 includes the following step A-1:

Step A-1: when the matching point includes a reference time, obtaining a sampling time closest to the reference time from a target set as a target time among the sampling times included in the matching point except the reference time;

Wherein, in the case where the reference time is a first sampling time, the target set includes the second sampling time;

In the case where the reference time is a second sampling time, the target set includes the first sampling time.

It should be noted that the above-mentioned reference time can be predetermined, for example, the predetermined reference time is the number of the multiple first sampling times obtained in step 101, or the number of the multiple second sampling times obtained in step 101. Exemplarily, the reference time is the first time of the second sampling times (that is, the second sampling times include , , , … The reference time is ), or the reference time is the last time in the first sampling time (that is, the first sampling time includes , , , … The reference time is ).

From the above, it can be seen that in an embodiment of the present application, a reference moment can be determined from the first sampling moment, and then a target moment that is closest to the reference moment can be determined in the target set formed by the second sampling moment, so that the reference moment and the target moment belong to the above matching point; or, a reference moment can be determined from the second sampling moment, and then a target moment that is closest to the reference moment can be determined in the target set formed by the first sampling moment, so that the reference moment and the target moment belong to the above matching point.

In an optional embodiment of the present application, in the above step A-1, obtaining the sampling time closest to the reference time from the target set includes the following step B-1:

Step B-1: traverse each sampling moment in the target set until a sampling moment that meets the target condition is obtained, and stop traversing, and determine the sampling moment that meets the target condition as the sampling moment in the target set that is closest to the reference moment;

The target conditions include: , represents the reference time, represents the i-th sampling time in the target set, represents the sampling frequency of the working mode to which the sampling moments included in the target set belong, Represents a constant.

It should be noted that the fabs function is a function that finds the absolute value, that is, Representation calculation The absolute value of .

Exemplarily, the first sampling moment includes , , , … , the second sampling moment includes , , , … , and the reference time is , you need to , , , … Each first sampling moment in is substituted into the inequality included in the above target condition in order from back to front to determine whether the condition is met, that is, first Substituting the inequality included in the target condition, we get , if the inequality does not hold, then Substituting the inequality included in the target condition, we get , if this inequality holds, then Distance from the reference time Otherwise, continue to substitute the next first sampling moment. It should be noted that in this case, is the sampling frequency in the first working mode.

or,

Exemplarily, the first sampling moment includes , , , … , the second sampling moment includes , , , … , and the reference time is , you need to , , , … Each second sampling moment in is substituted into the inequality included in the above target condition in order from front to back to determine whether the condition is met, that is, first Substituting the inequality included in the target condition, we get , if the inequality does not hold, then Substituting the inequality included in the target condition, we get , if this inequality holds, then Distance from the reference time Otherwise, continue to substitute the next second sampling moment. It should be noted that in this case, is the sampling frequency in the second working mode.

In an optional embodiment of the present application, the deviation parameter includes: an ambiguity constant correction value and an ambiguity variable correction value; the above step 103 of "determining the deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode according to the sampling data at the sampling time included in the matching point" includes the following steps C-1 to C-2:

Step C-1: According to the first formula , determine the ambiguity constant correction value deltaN0, where, represents the sampling data corresponding to the target time, Indicates the sampling data corresponding to the reference time;

Step C-2: According to the second formula , determine the ambiguity variable correction value ,in, represents the target time, represents the reference time.

Exemplarily, the first sampling moment includes , , , … , the second sampling moment includes , , , … , and the reference time is , the target time is ,but Equal to target time The sampling data minus the reference time The sampling data of = ;

or,

The first sampling moment includes , , , … , the second sampling moment includes , , , … , and the reference time is , the target time is ,but Equal to target time The sampling data minus the reference time The sampling data of = .

It should be noted that the ambiguity constant correction value and fuzzy variable correction value , which may be positive or negative.

In an optional embodiment of the present application, the deviation parameter includes: ambiguity constant correction value and fuzzy variable correction value In the above step 104, the step of “correcting the sampling data at the second sampling time according to the deviation parameter” includes the following step D-1:

Step D-1: According to the third formula , correcting the sampling data at the second sampling moment;

in, represents the sampling data at the mth second sampling moment, express The calibration data, represents the mth second sampling moment, represents the q+mth first sampling moment, q represents the ranking of the reference moment in the target sorting, and the target sorting is the sorting from front to back of the sampling moments belonging to the same working mode as the reference moment.

Exemplarily, the first sampling moment includes , , , … , the second sampling moment includes , , , … , and the reference time is , the target time is ,but:

When correcting the sampling data of the first and second sampling moments, ;

When correcting the sampling data at the second sampling moment, ;

The same applies when correcting the sampling data at other subsequent second sampling moments.

Alternatively, the first sampling moment includes , , , … , the second sampling moment includes , , , … , and the reference time is , the target time is ,but:

When correcting the sampling data at the third second sampling moment, ;

When correcting the sampling data at the 4th second sampling moment, ;

The same applies when correcting the sampling data at other subsequent second sampling moments.

In an optional embodiment of the present application, the first working mode is an open-loop mode, and the second working mode is a closed-loop mode; or, the first working mode is a closed-loop mode, and the second working mode is an open-loop mode.

It can be seen from this that when the occultation detection mode switches from open-loop mode to closed-loop mode, or from closed-loop mode to open-loop mode, the data correction method for occultation detection of the embodiment of the present application can be used to perform data correction.

The following specifically introduces the specific implementation of the data correction method for occultation detection in the embodiment of the present application by switching from the open-loop mode to the closed-loop mode, and from the closed-loop mode to the open-loop mode.

Implementation method 1: Switching from open-loop mode to closed-loop mode, and using the first sampling moment of the closed-loop mode as the reference moment. This implementation method is mainly aimed at the scenario of low-orbit satellites carrying GNSS reflection receivers to detect ascending occultation events. The specific process is as follows: Steps 1.1 to 1.3:

Step 1.1: The occultation receiver receives the rising occultation signal by first tracking the signal below 10 km in OL mode, and then tracking the signal above 10 km in PLL mode. The open-loop and closed-loop connection sequence is open-loop-closed-loop. As shown in Figure 2, the open-loop effective carrier phase observation value sequence is recorded as Y1, Y2, ..., Yn, and the open-loop sampling time sequence is , , ..., ; The closed-loop effective carrier phase observation value sequence is X1, X2, ..., Xn, and the closed-loop sampling time sequence is , , ..., , n is a positive integer.

Here, the first effective observation time (i.e., sampling time) of the closed-loop atmospheric occultation carrier phase observation is determined ),by Taking the time as the reference, traverse the open-loop sampling time sequence from back to front until the time that satisfies the following inequality (1) is obtained. The open-loop sampling time that satisfies the following inequality (1) is the observation time point closest to the closed-loop atmospheric occultation carrier phase observation time. .

(1)

in, represents the i-th open-loop sampling moment, represents the sampling frequency of the occultation receiver in open-loop mode, Represents a constant, such as It can be 4.

Step 1.2: Fix the matching points output from step 1.1 (i.e. and )’s closed-loop and open-loop carrier observations, and calculate the ambiguity constant corrections and ambiguity variable corrections.

Specifically, the first closed-loop observation time recorded in step 1.1 can be used The closest open-loop observation time point matching the phase X1 The ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN are calculated with the corresponding open-loop carrier phase observation value Yk and formula (2) and formula (3).

(2)

(3)

Step 1.3: Correct the closed-loop carrier phase observation value by using the ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN obtained in step 1.2 and the following formula (4).

(4)

in, represents the jth closed-loop carrier phase observation value, express The corrected value, represents the jth closed-loop sampling moment, Indicates the 1+jth open-loop sampling moment.

Implementation method 2: Switching from open-loop mode to closed-loop mode, and using the last sampling time of the open-loop mode as the reference time. This implementation method is mainly aimed at the scenario of low-orbit satellites carrying GNSS reflection receivers to detect ascending occultation events. The specific process is as follows: Steps 2.1 to 2.3:

Step 2.1: The occultation receiver receives the rising occultation signal by first tracking the signal below 10 km in OL mode, and then tracking the signal above 10 km in PLL mode. The open-loop and closed-loop connection sequence is open-loop-closed-loop. As shown in Figure 3, the open-loop effective carrier phase observation value sequence is recorded as Y1, Y2, ..., Yn, and the open-loop sampling time sequence is , , ..., ; The closed-loop effective carrier phase observation value sequence is X1, X2, ..., Xn, and the closed-loop sampling time sequence is , , ..., , n is a positive integer.

Here, the last valid observation time (i.e., sampling time) of the open-loop atmospheric occultation carrier phase observation is determined. ),by Taking the time as the benchmark, traverse the closed-loop sampling time series until the time that satisfies the following inequality (5) is obtained. The closed-loop sampling time that satisfies the following inequality (5) is the observation time point closest to the closed-loop atmospheric occultation carrier phase observation time. .

(5)

in, represents the jth closed-loop sampling moment, represents the sampling frequency of the occultation receiver in closed-loop mode, Represents a constant, such as It can be 4.

Step 2.2: Fix the matching points output from step 2.1 (i.e. and ) and calculate the ambiguity constant correction value and ambiguity variable correction value.

Specifically, the last open-loop observation time recorded in step 2.1 can be used The closest closed-loop observation time point that matches the phase Yn The ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN are calculated with the corresponding closed-loop carrier phase observation value Xk and formula (6) and formula (7).

(6)

(7)

Step 2.3: Correct the closed-loop carrier phase observation value by using the ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN obtained in step 2.2 and the following formula (8).

(8)

in, represents the jth closed-loop carrier phase observation value, express The corrected value, represents the jth closed-loop sampling moment, Indicates the n+jth open-loop sampling moment.

Implementation method 3: Switch from closed-loop mode to open-loop mode, and use the first sampling moment of the open-loop mode as the reference moment. This implementation method mainly targets the scenario where a low-orbit satellite carries a GNSS reflection receiver to detect a descending occultation event. The specific process is as follows: Steps 3.1 to 3.4:

Step 3.1: The occultation receiver receives the rising occultation signal by first tracking the signal above 10 km in PLL working mode, and then tracking the signal below 10 km in OL working mode. The open-closed loop connection sequence is closed-loop-open-loop. As shown in Figure 4, the closed-loop effective carrier phase observation value sequence is X1, X2, ..., Xn, and the closed-loop sampling time sequence is , , ..., , the open-loop effective carrier phase observation value sequence is recorded as Y1, Y2, ..., Yn, and the open-loop sampling time sequence is , , ..., , n is a positive integer.

Here, the first valid observation time (i.e., sampling time) of the open-loop atmospheric occultation carrier phase observation is determined ),by Taking the time as the reference, traverse the closed-loop sampling time series from back to front until the time that satisfies the following inequality (9) is obtained. The closed-loop sampling time that satisfies the following inequality (9) is the observation time point closest to the open-loop atmospheric occultation carrier phase observation time. .

(9)

in, represents the jth closed-loop sampling moment, represents the sampling frequency of the occultation receiver in closed-loop mode, Represents a constant, such as It can be 4.

Step 3.2: Fix the matching points output from step 3.1 (i.e. and ) and calculate the ambiguity constant correction value and ambiguity variable correction value.

Specifically, the first open-loop observation time recorded in step 3.1 can be used The closest closed-loop observation time point matching the phase Y1 The ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN are calculated with the corresponding closed-loop carrier phase observation value Xk and formula (10) and formula (11).

(10)

(11)

Step 3.3: Correct the open-loop carrier phase observation value by using the ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN obtained in step 3.2 and the following formula (12).

(12)

in, represents the i-th open-loop carrier phase observation value, express The corrected value, represents the i-th open-loop sampling moment, Indicates the 1+ith closed-loop sampling moment.

Implementation method 4: Switching from closed-loop mode to open-loop mode, and using the last sampling moment of the closed-loop mode as the reference moment. This implementation method is mainly aimed at the scenario of low-orbit satellites carrying GNSS reflection receivers to detect descending occultation events. The specific process is as follows: Steps 4.1 to 4.3:

Step 4.1: The occultation receiver receives the rising occultation signal by first tracking the signal above 10 km in PLL working mode, and then tracking the signal below 10 km in OL working mode. The open-closed loop connection sequence is closed-loop-open-loop. As shown in Figure 5, the closed-loop effective carrier phase observation value sequence is X1, X2, ..., Xn, and the closed-loop sampling time sequence is , , ..., , the open-loop effective carrier phase observation value sequence is recorded as Y1, Y2, ..., Yn, and the open-loop sampling time sequence is , , ..., , n is a positive integer.

Here, the last valid observation time (i.e., sampling time) of the closed-loop atmospheric occultation carrier phase observation is determined. ),by The time is taken as the reference, and the open-loop sampling time sequence is traversed until the time that satisfies the following inequality (13) is obtained. The open-loop sampling time that satisfies the following inequality (13) is the observation time point closest to the closed-loop atmospheric occultation carrier phase observation time. .

(13)

in, represents the i-th open-loop sampling moment, represents the sampling frequency of the occultation receiver in open-loop mode, Represents a constant, such as It can be 4.

Step 4.2: Fix the matching points output from step 4.1 (i.e. and )’s closed-loop and open-loop carrier observations, and calculate the ambiguity constant corrections and ambiguity variable corrections.

Specifically, the last closed-loop observation time recorded in step 4.1 can be used The closest open-loop observation time point that matches the phase Xn, The ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN are calculated with the corresponding closed-loop carrier phase observation value Yk and formula (14) and formula (15).

(14)

(15)

Step 4.3: Correct the open-loop carrier phase observation value by using the ambiguity constant correction value deltaN0 and the ambiguity variable correction value dotN obtained in step 4.2 and the following formula (16).

(16)

in, represents the i-th open-loop carrier phase observation value, express The corrected value, represents the i-th open-loop sampling moment, Indicates the n+ith closed-loop sampling moment.

It can be seen from the above-mentioned embodiments 1 to 4 that the embodiments of the present application can calculate the ambiguity constant correction value and the ambiguity variable correction value based on the open-loop and closed-loop carrier phase observation values corresponding to the matching points by traversing the matching points of the working mode before switching and the working mode after switching, and then correct the carrier phase observation value in the working mode after switching based on the ambiguity constant correction value and the ambiguity variable correction value. Therefore, the embodiments of the present application have the following advantages:

(1) Only the received carrier phase observations are operated, and no additional occultation observation data are required;

(2) The algorithm is time matching and one-dimensional calculation. The algorithm is simple and convenient for fast connection between open and closed loops.

(3) The ambiguity constant correction value and the ambiguity variable correction value are taken into account, so that the carrier phase during the open-closed loop switching is more accurate.

(4) Data correction can avoid the problem of discontinuous jumps in the calculation of the atmospheric additional phase in occultation processing.

To sum up, in order to overcome the ambiguity jump problem of atmospheric occultation carrier phase connection during the switching process between PLL working mode and OL working mode, the embodiments of the present application provide a data correction method for occultation detection. This method can connect GNSS open-loop atmospheric occultation carrier phase and closed-loop atmospheric occultation carrier phase data, and has the characteristics of fast connection speed, high carrier phase accuracy during switching, simple algorithm, and continuous and seamless connection.

The above describes the data correction method for occultation detection provided by the embodiment of the present application. The following describes the data correction device for occultation detection provided by the embodiment of the present application.

In a second aspect, an embodiment of the present application provides a data correction device for occultation detection, as shown in FIG6 , the device comprising:

An acquisition module 601 is used to acquire a first sampling moment and a second sampling moment, wherein the first sampling moment includes a sampling moment in a first working mode of occultation detection, and the second sampling moment includes a sampling moment in a second working mode of occultation detection;

A matching module 602 is used to determine a matching point between the first sampling moment and the second sampling moment, wherein the matching point includes the first sampling moment and the second sampling moment whose interval time is less than a target threshold;

A parameter determination module 603, configured to determine a deviation parameter between the sampled data in the first working mode and the sampled data in the second working mode according to the sampled data at the sampling moment included in the matching point;

The correction module 604 is used to correct the sampling data at the second sampling time according to the deviation parameter.

In an optional embodiment of the present application, the matching module 602 includes:

A matching submodule, configured to obtain, when the matching point includes a reference time, a sampling time closest to the reference time from a target set as a target time among the sampling times included in the matching point except the reference time;

Wherein, in the case where the reference time is a first sampling time, the target set includes the second sampling time;

In the case where the reference time is a second sampling time, the target set includes the first sampling time.

In an optional embodiment of the present application, the reference time is the first time of the second sampling time, or the reference time is the last time of the first sampling time.

In an optional embodiment of the present application, the matching submodule obtains the sampling time closest to the reference time from the target set, specifically for:

Traversing each sampling moment in the target set until a sampling moment that satisfies a target condition is obtained, and stopping the traversal, and determining the sampling moment that satisfies the target condition as the sampling moment in the target set that is closest to the reference moment;

The target conditions include: , represents the reference time, represents the i-th sampling time in the target set, represents the sampling frequency of the working mode to which the sampling moments included in the target set belong, Represents a constant.

In an optional embodiment of the present application, the deviation parameter includes: an ambiguity constant correction value and an ambiguity variable correction value; the parameter determination module 603 is specifically used to:

According to the first formula , determine the ambiguity constant correction value deltaN0, where, represents the sampling data corresponding to the target time, Indicates the sampling data corresponding to the reference time;

According to the second formula , determine the ambiguity variable correction value ,in, represents the target time, represents the reference time.

In an optional embodiment of the present application, the deviation parameter includes: ambiguity constant correction value and fuzzy variable correction value ;

In an optional embodiment of the present application, the correction module 604 is specifically used for:

According to the third formula , correcting the sampling data at the second sampling moment;

in, represents the sampling data at the mth second sampling moment, express The calibration data, represents the mth second sampling moment, represents the q+mth first sampling moment, q represents the ranking of the reference moment in the target sorting, and the target sorting is the sorting from front to back of the sampling moments belonging to the same working mode as the reference moment.

In an optional embodiment of the present application, the first operating mode is an open-loop mode, and the second operating mode is a closed-loop mode;

or,

The first operating mode is a closed-loop mode, and the second operating mode is an open-loop mode.

As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

In a third aspect, an embodiment of the present application provides an occultation receiver, comprising the above-mentioned data correction device for occultation detection.

In a fourth aspect, an embodiment of the present application further provides an electronic device, as shown in FIG7 , the electronic device may include: a processor 710, a communications interface 720, a memory 730, and a communication bus 740, wherein the processor 710, the communications interface 720, and the memory 730 communicate with each other via the communication bus 740. The processor 710 may call the logic instructions in the memory 730, and the processor 710 is used to execute the above-mentioned steps of data correction of occultation detection.

In addition, the logic instructions in the above-mentioned memory 730 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the various processes of the data correction method embodiment of the above-mentioned occultation detection are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive Solid State Disk (SSD)), etc.

It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

The above description is only a preferred embodiment of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims (13)

1. A data correction method for occultation detection, characterized in that the method comprises: Acquire a first sampling time and a second sampling time, wherein the first sampling time includes a sampling time in a first working mode of occultation detection, and the second sampling time includes a sampling time in a second working mode of occultation detection; Determine a matching point between the first sampling moment and the second sampling moment, wherein the matching point includes the first sampling moment and the second sampling moment whose interval time is less than a target threshold; According to the sampling data at the sampling time included in the matching point, the deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode is determined, wherein the deviation parameter includes: an ambiguity constant correction value and an ambiguity variable correction value, according to the first formula , determine the ambiguity constant correction value deltaN0, Represents the sampling data corresponding to the target time, Represents the sampling data corresponding to the reference time, according to the second formula , determine the ambiguity variable correction value , represents the target time, represents the reference time, the reference time is the first sampling time included in the matching point, and the target time is the second sampling time included in the matching point, or the reference time is the second sampling time included in the matching point, and the target time is the first sampling time included in the matching point; According to the third formula , correct the sampling data at the second sampling time, wherein, represents the sampling data at the mth second sampling moment, express The calibration data, represents the mth second sampling moment, represents the q+mth first sampling moment, q represents the ranking of the reference moment in the target sorting, and the target sorting is the sorting from front to back of the sampling moments belonging to the same working mode as the reference moment. 2. The method according to claim 1, characterized in that the determining the matching point between the first sampling time and the second sampling time comprises: In the case where the matching point includes the reference time, obtaining a sampling time closest to the reference time from the target set as the target time among the sampling times included in the matching point except the reference time; Wherein, in the case where the reference time is a first sampling time, the target set includes the second sampling time; In the case where the reference time is a second sampling time, the target set includes the first sampling time. 3 . The method according to claim 2 , wherein the reference time is the first time of the second sampling time, or the reference time is the last time of the first sampling time. 4. The method according to claim 2, characterized in that the step of obtaining the sampling time closest to the reference time from the target set comprises: Traversing each sampling moment in the target set until a sampling moment that satisfies a target condition is obtained, and stopping the traversal, and determining the sampling moment that satisfies the target condition as the sampling moment in the target set that is closest to the reference moment; The target conditions include: , represents the reference time, represents the i-th sampling time in the target set, represents the sampling frequency of the working mode to which the sampling moments included in the target set belong, Represents a constant. 5. The method according to claim 1, characterized in that the first working mode is an open-loop mode, and the second working mode is a closed-loop mode; or, The first operating mode is a closed-loop mode, and the second operating mode is an open-loop mode. 6. A data correction device for occultation detection, characterized in that the device comprises: An acquisition module, configured to acquire a first sampling moment and a second sampling moment, wherein the first sampling moment includes a sampling moment in a first working mode of occultation detection, and the second sampling moment includes a sampling moment in a second working mode of occultation detection; A matching module, configured to determine a matching point between the first sampling moment and the second sampling moment, wherein the matching point includes a first sampling moment and a second sampling moment whose interval time is less than a target threshold; A parameter determination module is used to determine the deviation parameter between the sampling data in the first working mode and the sampling data in the second working mode according to the sampling data at the sampling time included in the matching point, wherein the deviation parameter includes: a fuzzy constant correction value and a fuzzy variable correction value, according to the first formula , determine the ambiguity constant correction value deltaN0, Represents the sampling data corresponding to the target time, Represents the sampling data corresponding to the reference time, according to the second formula , determine the ambiguity variable correction value , represents the target time, represents the reference time, the reference time is the first sampling time included in the matching point, and the target time is the second sampling time included in the matching point, or the reference time is the second sampling time included in the matching point, and the target time is the first sampling time included in the matching point; A correction module is used to correct the , correct the sampling data at the second sampling time, wherein, represents the sampling data at the mth second sampling moment, express The calibration data, represents the mth second sampling moment, represents the q+mth first sampling moment, q represents the ranking of the reference moment in the target sorting, and the target sorting is the sorting from front to back of the sampling moments belonging to the same working mode as the reference moment. 7. The device according to claim 6, characterized in that the matching module comprises: A matching submodule, configured to, when the matching point includes the reference time, obtain, from a target set, a sampling time closest to the reference time as the target time among the sampling times included in the matching point except the reference time; Wherein, in the case where the reference time is a first sampling time, the target set includes the second sampling time; In the case where the reference time is a second sampling time, the target set includes the first sampling time. 8 . The device according to claim 7 , wherein the reference time is the first time of the second sampling time, or the reference time is the last time of the first sampling time. 9. The device according to claim 7, characterized in that the matching submodule obtains the sampling time closest to the reference time from the target set, specifically for: Traversing each sampling moment in the target set until a sampling moment that satisfies a target condition is obtained, and stopping the traversal, and determining the sampling moment that satisfies the target condition as the sampling moment in the target set that is closest to the reference moment; The target conditions include: , represents the reference time, represents the i-th sampling time in the target set, represents the sampling frequency of the working mode to which the sampling moments included in the target set belong, Represents a constant. 10. The device according to claim 6, characterized in that the first working mode is an open-loop mode, and the second working mode is a closed-loop mode; or, The first operating mode is a closed-loop mode, and the second operating mode is an open-loop mode. 11. An occultation receiver, characterized by comprising the data correction device for occultation detection according to any one of claims 6 to 10. 12. An electronic device, characterized in that it comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; A processor, for implementing the steps of the data correction method for occultation detection as claimed in any one of claims 1 to 5 when executing the program stored in the memory. 13. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the data correction method for occultation detection according to any one of claims 1 to 5 are implemented.